Information Technology

4 Ways Artificial Intelligence Can Improve Your Marketing (Plus 10 Provider Suggestions)


There are over 2.6 billion active social media users. Among them are your customers and potential customer. The question is, how to reach them! In today's fast-paced digital landscape, artificial intelligence can help your business create more effective marketing and social media strategies. AI can help you improve the consumer journey and change the way you attract, capture and nurture leads.

IIT Hyderabad becomes India's first Institute to launch BTech in Artificial Intelligence


Indian Institute of Technology Hyderabad is launching a full-fledged BTech Program in Artificial Intelligence (AI) from the coming Academic Year (2019-2020). It has become the first Indian Educational Institution to offer such a full-fledged BTech program in AI and likely the third institute globally - after Carnegie Mellon University and Massachusetts Institute of Technology (MIT), both of which are in the US. The Course will have an intake of around 20 students who can take the program through the JEE-Advanced. The mission of the Department of Artificial Intelligence, IIT Hyderabad, is to produce students with a sound understanding of the fundamentals of theory and practice of Artificial Intelligence and Machine Learning. It also aims to enable students to become leaders in the industry and academia nationally and internationally and meet the pressing demands of the nation in the areas of AI and Machine Learning.

Face-Scanning A.I. Can Help Doctors Spot Unusual Genetic Disorders Digital Trends


Facial recognition can help unlock your phone. Could it also be able to play a far more valuable role in people's lives by identifying whether or not a person has a rare genetic disorder, based exclusively on their facial features? DeepGestalt, an artificial intelligence built by the Boston-based tech company FDNA, suggests that the answer is a resounding "yes." The algorithm is already being used by leading geneticists at more than 2,000 sites in upward of 130 countries around the world. In a new study, published in the journal Nature Medicine, researchers show how the algorithm was able to outperform clinicians when it came to identifying diseases.

Using AI To Drive High-Converting Predictive Marketing


Everyone knows the saying: "A picture is worth a thousand words." In today's world of social posting, it's never been truer. But how do you predict which of those "thousand words" are truly relevant to your customer? To drive high conversion ratios, predictive marketing needs to target precisely relevant offers to attract and engage each customer individually. As marketers, we typically use experimentation, A/B testing or focus groups to assess relevance.

Microsoft CTO: Understanding AI is part of being an informed citizen in the 21st century


Microsoft CTO Kevin Scott believes understanding AI in the future will help people be better citizens. "I think to be a well-informed citizen in the 21st century, you need to know a little bit about this stuff [AI] because you want to be able to participate in the debates. You don't want to be someone to whom AI is sort of this thing that happens to you. You want to be an active agent in the whole ecosystem," he said. In an interview with VentureBeat in San Francisco this week, Scott shared his thoughts on the future of AI, including facial recognition software and manufacturing automation.

Jacques Ludik on LinkedIn: "#ai #innovation #machinelearning #digitaltransformation #artificialintelligence Cortex Logic"


Dr Jacques Ludik is a smart technology entrepreneur, AI expert, investor & ecosystem builder and currently Founder & President of Machine Intelligence Institute of Africa (MIIA), Founder & CEO of Cortex Logic, Founder of Bennit AI, Founder of SynerG, The Talent Index, & aiTRADE Systems, and investor in The Student Hub (ERAOnline). He holds a Ph.D. in Computer Science (AI) with many publications and has 25 years' experience in Machine / Artificial Intelligence (AI) & Data Science and its applications. MIIA is an innovative community & accelerator for Machine Intelligence & Data Science Research & Applications to help transform Africa, whereas Cortex Logic is an AI company that provides an AI Engine for Business, advances AI and builds end-to-end AI solutions for a range of industries. Bennit A.I. is an intelligent virtual production assistant/advisor for manufacturing. For businesses to thrive in the smart technology era, they need to be agile, innovative and adapt quickly to stay relevant, given the swift pace of change and disruption to business and society.

Stung by Cambridge Analytica debacle, Facebook backs election integrity, AI initiatives in Germany

The Japan Times

MUNICH, GERMANY - Facebook has launched German initiatives to defend election integrity and examine the ethics of artificial intelligence (AI), its operations chief said on Sunday, seeking to convince skeptics it is serious about privacy and democracy. The world's largest social network had a tough 2018 as it was buffeted by revelations that U.K. consultancy Cambridge Analytica had improperly acquired data on millions of its U.S. users to target election advertising. Founder Mark Zuckerberg has been grilled by lawmakers on the data lapses and, according to newspaper reports, U.S. regulators are discussing fining Facebook for violating a binding agreement to protect the privacy of its users. "We are not the same company that we were in 2016 or even a year ago," Chief Operating Officer Sheryl Sandberg told the DLD Munich technology conference. "We have a fundamentally different approach to how we run our company today."

Spanning the reality gap between AI and Industry 4.0


Artificial intelligence has become a booming trend in the industrial sector these days, as automation and optimization continue to be the primary focus of the digital revolution. In this article, we will take a look at the state of the art computer vision techniques that have generated a lot of excitement in AI community in the last few years, and are considered to be industry-ready and are sure to have a significant and practical impact for industrial use cases. Some of these techniques demonstrate incremental yet incredible advancements in performance, surpassing human level performance and thus surpassing precision and reliability standards expected by most industries. The incredible advancement in basic computer vision tasks, such as image classification, have made it feasible to reliably combine multiple techniques to create new, compound techniques that enable entirely new use cases that have never been explored in industrial environments before. That being said, these new techniques have demonstrated that is it possible to obtain precision and reliability results comparable to those that would otherwise only be obtainable with specialized systems that are very hardware intensive.



We present graph wavelet neural network (GWNN), a novel graph convolutional neural network (CNN), leveraging graph wavelet transform to address the shortcomings of previous spectral graph CNN methods that depend on graph Fourier transform. Different from graph Fourier transform, graph wavelet transform can be obtained via a fast algorithm without requiring matrix eigendecomposition with high computational cost. Moreover, graph wavelets are sparse and localized in vertex domain, offering high efficiency and good interpretability for graph convolution. The proposed GWNN significantly outperforms previous spectral graph CNNs in the task of graph-based semi-supervised classification on three benchmark datasets: Cora, Citeseer and Pubmed. The codebase is implemented in Python 3.5.2.

AI in 2018: More Deep Learning Extensions and Crazy Rich Bayesians


This is the second installment of a three-part piece on the advances made in artificial intelligence in 2018, by Yves Bergquist, founder and CEO of AI company Corto, and director of the AI and Neuroscience in Media Project at the Entertainment Technology Center at the University of Southern California (ETC@USC). Part one can be read here. With one new academic paper publisher every half hour or so in 2018, machine learning is still -- and by far -- the most vigorous domain of AI. And within machine learning, Deep Learning (also called Deep Neural Networks) still dominates the field. This year saw a lot of extensions of DL to new areas, especially natural language.